With the explosive growth of Internet broadband access and the increasingly diverse types of backbone links with long delays, it appears likely that new network protocols will continue to be developed to accommodate new network and application behaviors. With the quickly increasing growth of network bandwidth, satellite networks with large delay and wireless networks with multihops, backbone networks with the characteristics of high bandwidth and large delay are appeared in the internet, which forming the high bandwidth delay product (High Bandwidth Delay Product, HBDP) networks. Under the situation that the increasing of bandwidth and delay of uniflow, the effectiveness of the congestion control mechanism for the network transmission need to be guaranteed. The traditional protocol cannot satisfy the increasing transmission demand. Thus, according to the features of the high speed network, the high-efficiency transmission mechanism has become the key direction of the researches.
The researchers have put forward multiple kinds of improved acceleration transmission method of TCP and UDP. Therein, to solve the conservative additive increase multiplicative decrease strategy problem of TCP, the researchers adjust the congestion window program and protocol the improved new protocols based on TCP but different mechanisms are adopted for them, which include HighSpeed TC, Scalable TCP, Fast TCP, BIC, CUIBIC and HTCP. These algorithms make the increasing process of congestion window speed up through congestion control algorithm, which modifies the end system to obtain high throughput capacity. Consequently, the transmission performance of high speed network can be improved.
The window adjustment algorithm based on the improved protocol of TCP can be conclude as: when receive ACK feedback,
      W    =          W      +                        f          ⁡                      (            x            )                          W              ;when packet loss events happened, W=(1−g(x))·W. Therein, W refers to the congestion window size, f(x) refers to the additive function adopted by the sending side when receiving ACK packet, g(x) refers to the multiplicative function adopted when packet loss events occurs and the variable x refers to the implicit expression feedback factor may be selected by congestion adjustment function. Different feedback factors are selected according to the design of different f(x) and g(x).
The improved TCP designs different function changes through selecting the implicit expression feedback factor based on packet loss, time delay, or packet loss and time delay at the same time. Although the improved TCP has gotten certain bandwidth occupancy, this kind of mechanism which is based on the precise exploration of network situation is easily affected by the factors such as RTT change, multiple data traffic competition and background traffic, etc., which cannot obtain high bandwidth occupancy. Moreover, in the network with long delays, the unfairness of throughput capacity resulted by different RTT between the TCP is magnified, in which the problems such as the bandwidth distribution which cannot be convergent to the fairness or the unstable fairness. What's more, the packet loss recovery mechanism of TCP will result in the frequent shaking of TCP flow, making the queue buffer in the router unstable and reducing the transmission performance of high bandwidth delay product networks.
The TCP protocols based on the learnable characteristics such as the Remy algorithm which is proposed by Keith Winstein et al. uses the algorithm of offline automated learning to generate the congestion control algorithm that can maximize the expected value of target function through inputting all kinds of parameter models (such as the bottleneck link rate, time delay, the upper and lower bounds of multiplexing parameter, traffic model, network scenarios and so on). As the TCP has mechanism limitation itself and at the same time, this algorithm can only be used actually after the offline learning training is conducted. It cannot truly conduct perception on the network at real time, whose ease of use is relatively bad.
The reliable transmission methods are based on the UDP protocol including RUDP, RTP, UDT, Verus and etc., which are the protocols that conduct reliable control in the application layer. RUDP offers a group of data service quality strengthening mechanism such as improving of congestion control, retransmission mechanism, desalination server algorithm and son on. RUDP uses the retransmission mechanism and congestion control algorithm which are similar to that of TCP; RTP protocol can serialize the packets but the RTP does not offer any mechanism to confirm the timely transmission or offer guarantee for other service quality (Quality of Service, QoS) itself; UDT combines the rate control and window (traffic) control, in which the former adjusts the period of transmission of the packets and the later limits the maximum packets which do not obtain the response and the parameters used in the rate control are updated through bandwidth evaluation technology. This method is still based on the precise exploration on the network situation, which has the same problems as that of precise exploration on the network situation to TCP. Verus protocol adjusts the window through establishing the model during short period for the relationship between the time delay and the window instead of conducting precise exploration on the network status, which is applicable for the environment which cannot accurately control and explore the network status (such as unstable delay) but is not good as UDT in the aspect of bandwidth utilization.
Invention Content
This invention aims to solve the technical problem which offers a kind of transmission method based on the learnable power model (hereafter referred to as Hita protocol) to satisfy the high speed and reliable transmission demand in the high speed network.
To solve the technical problem mentioned above, the technical program adopted by this invention is:
A kind of transmission method based on the learnable power efficiency model, which includes the steps as follows:                Step 1: Record the round trip time vector of all ACK packets received {right arrow over (D)}i and the sending window vector {right arrow over (W)}i, in which i means the current time period. Adopt the formula Dg,i=α·Dg,i−1+(1−α)·{right arrow over (D)}i to conduct weighting smooth processing on the round trip time vector {right arrow over (D)}i. Therein, i−1 refers to the last time period, α is the weighting smooth factor and Dg,i is the round trip time of maximum delay of ith time period after smoothing;        Step 2: Calculate the normalized time delay change rate Gi in accordance with the formula        
      G    i    =            (                                    D                          g              ,              i                                -                      D                          g              ,                              i                -                1                                                                          D                          g              ,              i                                +                      D                          g              ,                              i                -                1                                                        )        ⁢                  (                                            W                              g                ,                i                                      +                          W                              g                ,                                  i                  -                  1                                                                                        W                              g                ,                i                                      -                          W                              g                ,                                  i                  -                  1                                                                    )            .      Therein, Wg,i is the window size of the maximum time delay value of the ith time period;                Step 3: Calculate the network power estimation value Ee,i in accordance with the formula        
      E          e      ,      i        =                    T        i        Δ                    D        i              .  Δ refers to the sensitive factor of delay-throughput and Ti refers to the actual throughput of the ith time period, which are gotten through accumulation of the confirmed send window vector {right arrow over (W)}i in each time period. Di refers to all elements in the round trip time vector {right arrow over (D)}i of the i time period;                Step 4: Establish the corresponding relationship model between the corresponding network power capacity E of every data packet and the send window size W, which is defined as W(x+1)=f(E(x)+γ(x)). Therein, x is the time change parameter, i.e. time period i. W(x+1) is the congestion control window size of the next time period, f(x) is the window control function, E(x) is the estimation function of network power and γ(x) is the increase and decrease size of network power;        Step 5: Judge the changing trend of network status. When Gi>0 or        
                    D                  max          ,          i                            D        min              >    R    ,the network becomes congestion and the network power should correspondingly decrease in the next time period. When Gi≤0 and
                    D                  max          ,          i                            D        min              >    R    ,network becomes free and the network power should correspondingly increase in the next time period, which is
      E          e      ,              i        +        1              =      {                                                      E                              e                ,                i                                      -                          γ              2                                                                                          When                ⁢                                                                  ⁢                                                      D                                          max                      ,                      i                                                                            D                    min                                                              >              R                        ⁢                                                                                                                E                              e                ,                i                                      -                          γ              1                                                                          When              ⁢                                                          ⁢                              G                i                                      >            0                                                                          E                              e                ,                i                                      +                          γ              2                                                Otherwise                    in detail; Ee,i+1 is the network power estimation value of the i+1 time period, Dmax,i is the maximum element in the round trip time vector {right arrow over (D)}i of i time period, Dmin is the minimum element in the round trip time vector {right arrow over (D)}i and R is the maximum value of the link tolerance; γ1 and γ2 refer to the increase and decrease value of the network power. Through a large quantity of repeated experiments, the optimum values are selected;                Step 6: Calculate the Wi+1 window value according to Step 4 and Step 5;        Step 7: Divide every time period into n time slots. Every time slot is ms. After the i time period, the data sent within n−1 time slots is taken as a part of data to Wi+1. For instance, first n−1 time slots in every time period are used for the learnable model and the last time slot is used to send the remaining data. So the size of the data which shall be sent of the last time slot of the Wi+1 window is Wfin,i+1 and        
      W          fin      ,              i        +        1              =            max      ⁡              [                  0          ,                      (                                          W                                  i                  +                  1                                            -                                                                    n                    -                    2                                                        n                    -                    1                                                  ·                                  W                  i                                                      )                          ]              .  
According to the program mentioned above, in Step 1, the value of α is 0.875. According to the program mentioned above, the model W(x+1) is learned and gotten by adoption of the linear regression algorithm in the machine learning algorithm. The input parameters are the corresponding network carrying capacity E of every data packet and the send window size W of the i time period.
According to the program mentioned above, the value of γ1 is 2 ms and the value of γ2 is 3 ms.
According to the program mentioned above, every time slot length λ is 5 ms.
      n    =          ⌈                                    D            ⇀                    ave                λ            ⌉        ,in which {right arrow over (D)}ave refers to the mean value of all elements in the round trip time vector {right arrow over (D)}i.
According to the program mentioned above, if the network packet loss or time-out issue occurs, the multiplicative reduction mechanism with β as the multiplicative factor shall be conducted, i.e. Wi+1=β·Wi, in which β is the multiplicative reduction factor. And conduct the retransmission mechanism of the data packets to the traditional TCP. At this time, the window increases in the way of plusing 1.
According to the program mentioned above, the value of β is 0.7.
Being compared with the current technology, the beneficial effects of this invention are: 1) It has the feature of rapid convergence. Being compared with the traditional reliable transmission protocol, this invention follows the network status change through constantly learning of the feedback ACK within a certain time period, records the relationship between network energy efficiency and the window and establishes the model. Through this way, it can forecasts the dynamic change of the network and quickly adjust the window size of congestion control protocol. 2) Through adjusting the parameters which affect the delay and throughput in the model, this invention can make tradeoff between delay and throughput. In high speed networks, it can get closed to the best link bandwidth occupancy with lower end-to-end delay. The relatively traditional TCP or the reliable transmission protocol based on UCP has higher bandwidth occupancy rate and reduces the end-to-end delay of the transmission experience to the data packets at the same time. 3) This invention only needs to modify the end-to-end protocol of the application layer without the intermediate router or the network for configuration assistant. The proposed protocol is convention and easy to used and is also easy to be integrated into all kinds of application layer protocols based on the reliable transmission.